Search: “inference”

Fewer Tokens, More Self-Teaching: On-Policy Self-Distillation for Extreme Visual Token Reduction

arXiv:2609.32353v1 Announce Type: new Abstract: Visual token reduction is an effective way to accelerate multimodal large language models (MLLMs), but performance deteriorates rapidly under extremely

safetyarxiv-cs-cv

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Hardware

Fill2SR: Repurposing Inpainting Diffusion Transformers for Real-World Super-Resolution

DGX agent

arXiv:2609.33582v1 Announce Type: new Abstract: Recent real-world image super-resolution (SR) methods often adapt text-to-image (T2I) backbones with ControlNet-style branches or spatial conditioning t

hardwarearxiv-cs-cv

29 Sept 2026

Applications

FloodDiffusion 2: Efficient and Path Controllable Streaming Motion Generation

arXiv:2609.33167v1 Announce Type: new Abstract: We present FloodDiffusion 2 (FD2), an efficient and controllable framework that builds upon FloodDiffusion (FD1), a state-of-the-art streaming motion ge

applicationsarxiv-cs-cv

FlowTool: Controlling Tool Parameter in Image Retouching via Flow Matching

arXiv:2609.35673v1 Announce Type: new Abstract: Tool-based image editing (image retouching) is commonly formulated with autoregressive multimodal large language models (MLLMs) that sequentially genera

Focus and Supplement: Dual-Enhanced Vision Transformer for Multi-Class Anomaly Classification

arXiv:2609.33353v1 Announce Type: new Abstract: Multi-class anomaly classification in industrial vision remains challenging due to noisy/incomplete anomaly representations and the unknown number of an

Forest-Guided Semantic Transport for Label-Supervised Manifold Alignment

arXiv:2602.00974v2 Announce Type: replace Abstract: Label-supervised manifold alignment bridges the gap between unsupervised and correspondence-based paradigms by leveraging shared label information t

FORGE: Form-Optimal Routing of Grounded Evidence for Frozen LLM Agents

arXiv:2609.34358v1 Announce Type: new Abstract: In agentic AI systems, frozen foundation models are increasingly deployed as closed-weight API endpoints, making downstream adaptation possible only thr

FSS-UBrain: Multi-region Few-Shot Brain Tumor MRI Segmentation

arXiv:2609.32273v1 Announce Type: new Abstract: Accurate delineation of whole tumor (WT), tumor core (TC), and enhancing tumor (ET) from multimodal magnetic resonance imaging remains challenging under

Future Information-Directed Sampling for Bayesian Nonstationary Bandits

arXiv:2609.33981v1 Announce Type: new Abstract: Exploration--exploitation is a central trade-off in bandit learning. While classical algorithms such as upper confidence bound methods and Thompson Samp

FutureDuet: Decoupling Observation Access from Future Supervision in World Action Models

arXiv:2609.34362v1 Announce Type: new Abstract: World Action Models (WAMs) augment robot action generation with future visual supervision. Existing WAMs commonly fuse main and wrist observations into

local-aiarxiv-cs-ro

GeoCR: Learning a Generalist Cloud Removal Prior from Heterogeneous Observations

arXiv:2609.32510v1 Announce Type: new Abstract: Cloud removal methods are typically specialized to individual datasets and input configurations, limiting reuse across sensors, spectral bands, and obse

Goal-Conditioned Supervised Learning for Multi-Objective Recommendation

arXiv:2412.08911v4 Announce Type: replace Abstract: Multi-objective learning endeavors to concurrently optimize multiple objectives using a single model, aiming to achieve high and balanced performanc

researcharxiv-cs-lg

Groupwise Selective State-Space Filtering for Accurate and Streaming Action Boundary Detection

arXiv:2609.33400v1 Announce Type: new Abstract: Action boundary detection partitions untrimmed video into intervals without assigning action classes. We present a boundary-detection adapter operating

GuardPIBT: Counterfactually Gated Neural Guidance for Ultra-Large-Scale 3D Multi-Agent Path Finding

arXiv:2609.35267v1 Announce Type: new Abstract: Large-scale 3D multi-agent path finding becomes increasingly difficult under dense traffic. Priority Inheritance with Backtracking (PIBT) scales well, b

local-aiarxiv-cs-ro

GUIDE-FBO: Guidance via Uncertainty Intervention and Distributional Exchange for Federated Bayesian Optimization

arXiv:2609.35038v1 Announce Type: cross Abstract: Federated Bayesian Optimization (FBO) enables distributed agents to collaboratively optimize expensive black-box objectives without sharing raw local

agentsarxiv-cs-lg

Hardware-Aware Features for CUTLASS Kernel Selection

arXiv:2609.35587v1 Announce Type: new Abstract: GPU libraries such as CUTLASS expose tens of thousands of semantically equivalent kernels for a single operation, making exhaustive autotuning expensive

HGPTrans: Hierarchical Graph-Pooling Transolver for Automotive Aerodynamic Drag Coefficient Prediction

arXiv:2609.31765v1 Announce Type: new Abstract: Accurate and rapid prediction of the aerodynamic drag coefficient (C_D) is essential for vehicle design, particularly during early-stage styling iterati

local-aiarxiv-cs-cv

Humanoid Loco-Manipulation With Discrete VLA Model

model-releasesarxiv-cs-ro

arXiv:2609.35709v1 Announce Type: new Abstract: Vision-language-action (VLA) models using discrete action tokens have proven effective for controling robotic arms on manipulation tasks. For a humanoid

Applications

In-Token Learning for High-Fidelity Image Restoration via Diffusion Transformers

arXiv:2609.33523v1 Announce Type: new Abstract: We present In-Token Learning, an image restoration framework that adapts a pretrained diffusion transformer using conditional rectified flow matching. C

applicationsarxiv-cs-cv

Integrating Language Models into Listened and Imagined Speech Decoding from MEG

arXiv:2609.31997v1 Announce Type: new Abstract: Decoding imagined speech is an important goal for brain-computer interfaces but remains challenging due to weak neural responses, low signal-to-noise ra

researcharxiv-cs-lg

JET: Justification Evaluation in Transformer

arXiv:2609.33874v1 Announce Type: new Abstract: JET uses pretrained language and vision-language models to select among a finite set of answers without additional training. It evaluates candidate like

local-aiarxiv-cs-lg

Just MLPs: Efficient Visual State Reconstruction for Multimodal Language Models

arXiv:2609.34972v1 Announce Type: new Abstract: Long visual token sequences often account for a substantial fraction of the computational overhead in multimodal large language models~(MLLMs). Existing

Kafila: Serving Large Language Models on a Trusted Set of Heterogeneous Commodity Machines

arXiv:2609.34045v1 Announce Type: cross Abstract: Between them, the members of a research group or a circle of friends own several consumer computers, none large enough to run a capable large language

agentsarxiv-cs-lg

KeyRec: Bounded Visual Memory for Streaming and Long-Video Understanding

arXiv:2609.32182v1 Announce Type: new Abstract: Vision-language models are increasingly used to understand long videos and continuous streams. However, dense visual tokens accumulate with video durati

KiT: A Foundation Model for Financial Time-Series Forecasting using DiffusionTransformers

arXiv:2609.34507v1 Announce Type: cross Abstract: Financial candlestick forecasting is fundamental to quantitative investment, yet it remains exceptionally challenging due to extremely low signal-to-n

Knowledge-Driven XRD Phase Identification via Multi-View Retrieval and Explanation

arXiv:2609.31888v1 Announce Type: cross Abstract: X-ray diffraction (XRD) is a experimental technique for determining the phase composition and structure of crystalline materials. However, interpretin

researcharxiv-cs-lg

Hardware

KVCMAS: Efficient KV cache Correction for Shared Context in Multi-Agent Systems

arXiv:2609.34060v1 Announce Type: new Abstract: Prompt-specialized multi-agent systems enable multiple agents to share a model while performing complementary roles to solve complex tasks. However, age

hardwarearxiv-cs-lg

Large Language Models for Automated Cross-Domain Machine Learning Task Type Identification: A Benchmark Dataset and Evaluation

arXiv:2609.35335v1 Announce Type: new Abstract: Machine learning task type identification is essential for constructing valid ML pipelines, yet in practice it is typically specified manually. We inves

Learn Here, Move Less Elsewhere: Input-Conditioned Plasticity from Retained-Domain Activation Atlases

arXiv:2609.34478v1 Announce Type: new Abstract: Task-specific fine-tuning can rewrite a language model's answers beyond the training task, complicating updates that must preserve existing behavior. We

local-aiarxiv-cs-lg

Learning Geometrically-Grounded Amodal 3D Representations for View-Generalizable Robotic Manipulation

arXiv:2601.22988v2 Announce Type: replace Abstract: Real-world robotic manipulation requires visuomotor policies capable of robust 3D scene reasoning under varying camera viewpoints. While recent 3D-a

safetyarxiv-cs-ro

Learning Native Reflection in Unified Models with Interleaved Reinforcement Learning

arXiv:2609.35767v1 Announce Type: new Abstract: Unified multimodal models can both look at and render images, so in principle they can repair their own generations: diagnose what an image gets wrong,

Learning Through Game: Skewed Transfer of Tabular Knowledge to Strengthen Image Model

arXiv:2609.32272v1 Announce Type: cross Abstract: Multimodal tabular-image learning is gaining growing attention, yet it faces challenges due to tabular data unavailable at test time. A practical solu

Learning to Act under Visual Interruptions with Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2609.35003v1 Announce Type: new Abstract: Vision-language-action (VLA) models have demonstrated strong capabilities in robotic manipulation, but they are typically developed and evaluated with a

Applications

Learning to Generate Rigid Body Interactions with Video Diffusion Models

arXiv:2510.02284v4 Announce Type: replace Abstract: Recent video generation models have achieved remarkable progress and are now deployed in film, social media production, and advertising. Beyond thei

applicationsarxiv-cs-cv

Learning Transferable Sensor Models via Language-Informed Pretraining

arXiv:2603.11950v2 Announce Type: replace-cross Abstract: Multimodal language models have demonstrated strong semantic understanding and reasoning over physiological and behavioral signals captured fr

Learning What to Recall: Adaptive Multi-Cue Episodic Memory for World Models

arXiv:2609.34677v1 Announce Type: cross Abstract: World models predict future observations from current experience and actions, yet prediction can depend on observations seen far in the past. Episodic

Less Is More: Genetic Frame Selection for Efficient Novel View Synthesis

arXiv:2609.35573v1 Announce Type: new Abstract: Feed-forward novel view synthesis reconstructs a scene from many input images in a single forward pass, yet more views do not necessarily improve perfor

Less Sycophancy, Stronger Refusal? Lessons for AI Safety from Mechanistic Interpretability

arXiv:2609.35544v1 Announce Type: cross Abstract: Reliable refusal of harmful requests is essential to the safe deployment of language models. Because excessive eagerness to please users may undermine

LFPO: Likelihood-Free Policy Optimization for Masked Diffusion Models

arXiv:2603.01563v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has achieved remarkable success in improving autoregressive models, especially in domains requ

LLMs are General Asynchronous Agents

arXiv:2609.35427v1 Announce Type: new Abstract: Modern LLMs are increasingly capable as autonomous agents, but they follow sequential interaction cycles: read, think, reply or call tools, repeat. Many

LoCoVSR: Local Context Diffusion Posterior Sampling for Video Super-Resolution

arXiv:2609.32742v1 Announce Type: new Abstract: Video super-resolution (VSR) is an ill-posed inverse problem that aims to reconstruct a high-resolution (HR) video from a noisy, low-resolution (LR) ver

local-aiarxiv-cs-cv

Look Before You Judge: Training-Free Region Mining for Grounded and Explainable Deepfake Detection

arXiv:2609.35536v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can explain deepfake verdicts in natural language, but such explanations are not necessarily visually grounded

Tutorials

LVMT: Video Mask Transformer for Long-term Video Segmentation

arXiv:2609.34895v1 Announce Type: new Abstract: Existing online video segmentation methods struggle to track objects in long, complex videos with long-term occlusions. We hypothesize that this limitat

tutorialsarxiv-cs-cv

Machine learning for the LHC physics program: a 2025-2026 stocktake

arXiv:2609.32874v1 Announce Type: cross Abstract: The first sentence of this abstract--and the introduction to these proceedings--was authored by a human, but the bulk of this document was generated b

agentsarxiv-cs-lg

MechBench: Can AI Scientific Agents Discover Mechanisms Beyond Phenomenal Laws?

arXiv:2609.35515v1 Announce Type: cross Abstract: Scientific discovery requires not only recovering mathematical laws that describe observable behavior, but also identifying the mechanisms that genera

Model Casting and Low-Parameter Gating: Towards More Sparsely Activated FFNs

arXiv:2609.31975v1 Announce Type: new Abstract: This paper introduces model casting, a mid-training recipe that drastically sparsifies the activations within the Feed-Forward Network (FFN) layer. With

Motion Forcing: A Decoupled Framework for Robust Video Generation in Motion Dynamics

arXiv:2603.10408v2 Announce Type: replace Abstract: The ultimate goal of video generation is to satisfy a fundamental trilemma: achieving high visual quality, maintaining rigorous physical consistency

agentsarxiv-cs-cv

MotionSpaceFlow: Representation-Aware Flow Matching in Direct Motion Space

arXiv:2609.34190v1 Announce Type: new Abstract: Recent advances in diffusion and flow models have substantially improved text-driven human motion generation. Yet most methods generate in low-dimension